Dataset Information

Transcriptome analysis in a unique cohort of untreated primary tumors collected from diagnostic prostate needle biopsies (PNBX) of localized (M0) and metastatic (M1) cases

ABSTRACT: PNBX were collected from 99 patients treated in the VA Greater Los Angeles (GLA-VA) Healthcare System between 2000-2016

ORGANISM(S): Homo sapiens

PROVIDER: GSE147493 | GEO | 2020/03/26

REPOSITORIES: GEO

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Project description:Mathematical modeling of mutant transferrin-CRM107 molecular conjugates for cancer therapy. Yoon DJ1, Chen KY1, Lopes AM1, Pan AA1, Shiloach J2, Mason AB3, Kamei DT4. Author information 1 Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA. 2 Biotechnology Core Laboratory, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Health, Bethesda, MD 20892, USA. 3 Department of Biochemistry, University of Vermont College of Medicine, Burlington, VT 05405, USA. 4 Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA. Electronic address: kamei@seas.ucla.edu. Abstract The transferrin (Tf) trafficking pathway is a promising mechanism for use in targeted cancer therapy due to the overexpression of transferrin receptors (TfRs) on cancerous cells. We have previously developed a mathematical model of the Tf/TfR trafficking pathway to improve the efficiency of Tf as a drug carrier. By using diphtheria toxin (DT) as a model toxin, we found that mutating the Tf protein to change its iron release rate improves cellular association and efficacy of the drug. Though this is an improvement upon using wild-type Tf as the targeting ligand, conjugated toxins like DT are unfortunately still highly cytotoxic at off-target sites. In this work, we address this hurdle in cancer research by developing a mathematical model to predict the efficacy and selectivity of Tf conjugates that use an alternative toxin. For this purpose, we have chosen to study a mutant of DT, cross-reacting material 107 (CRM107). First, we developed a mathematical model of the Tf-DT trafficking pathway by extending our Tf/TfR model to include intracellular trafficking via DT and DT receptors. Using this mathematical model, we subsequently investigated the efficacy of several conjugates in cancer cells: DT and CRM107 conjugated to wild-type Tf, as well as to our engineered mutant Tf proteins (K206E/R632A Tf and K206E/R534A Tf). We also investigated the selectivity of mutant Tf-CRM107 against non-neoplastic cells. Through the use of our mathematical model, we predicted that (i) mutant Tf-CRM107 exhibits a greater cytotoxicity than wild-type Tf-CRM107 against cancerous cells, (ii) this improvement was more drastic with CRM107 conjugates than with DT conjugates, and (iii) mutant Tf-CRM107 conjugates were selective against non-neoplastic cells. These predictions were validated with in vitro cytotoxicity experiments, demonstrating that mutant Tf-CRM107 conjugates is indeed a more suitable therapeutic agent. Validation from in vitro experiments also confirmed that such whole-cell kinetic models can be useful in cancer therapeutic design. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dataset Information

Transcriptome analysis in a unique cohort of untreated primary tumors collected from diagnostic prostate needle biopsies (PNBX) of localized (M0) and metastatic (M1) cases

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